model{
  ## Likelihood
  for(i in 1:N){
    accept[i]~dbern(p[i])
    logit(p[i]) <- beta0 + inprod(beta[],X[i,])
    #+ b[X.b[i,1]] 
  }     
  ## Priors 
  beta ~ dmnorm(mu.beta,tau.beta)  # multivariate Normal prior
  beta0 ~ dnorm(0,0.0001)
  #for(j in 1:nb){
  #b[j] ~ dnorm(0, tau) 
  #}
  #tau <- pow(sigma,-2)
  #sigma ~ dunif(0,3)
}
